{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TGEDQW77YC3Q75LAPTY6HFXUIC","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"bcd52030a0c53a0721a2aa59df92549cec5c4338df1d1da3ed5a75f28be94567","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-08T04:16:28Z","title_canon_sha256":"d928473929eaf882f96065e5f44b24b069454a23a6e29388137d05eb40daeaf9"},"schema_version":"1.0","source":{"id":"1912.03612","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.03612","created_at":"2026-07-05T00:24:47Z"},{"alias_kind":"arxiv_version","alias_value":"1912.03612v1","created_at":"2026-07-05T00:24:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.03612","created_at":"2026-07-05T00:24:47Z"},{"alias_kind":"pith_short_12","alias_value":"TGEDQW77YC3Q","created_at":"2026-07-05T00:24:47Z"},{"alias_kind":"pith_short_16","alias_value":"TGEDQW77YC3Q75LA","created_at":"2026-07-05T00:24:47Z"},{"alias_kind":"pith_short_8","alias_value":"TGEDQW77","created_at":"2026-07-05T00:24:47Z"}],"graph_snapshots":[{"event_id":"sha256:56345667dfc275cd39d6db4ab148e9dcc4f068ffdc90167ea0f6528c8ba56745","target":"graph","created_at":"2026-07-05T00:24:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1912.03612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this report, we introduce the Winner method for HACS Temporal Action Localization Challenge 2019. Temporal action localization is challenging since a target proposal may be related to several other candidate proposals in an untrimmed video. Existing methods cannot tackle this challenge well since temporal proposals are considered individually and their temporal dependencies are neglected. To address this issue, we propose sparse 2D temporal adjacent networks to model the temporal relationship between candidate proposals. This method is built upon the recent proposed 2D-TAN approach. The sam","authors_text":"Houwen Peng, Jianlong Fu, Jiebo Luo, Le Yang, Songyang Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-08T04:16:28Z","title":"Learning Sparse 2D Temporal Adjacent Networks for Temporal Action Localization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.03612","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:25dfe20f2a70f267011e1ffc4678262d0ec6060ce07dd9587ed3d1c683189012","target":"record","created_at":"2026-07-05T00:24:47Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"bcd52030a0c53a0721a2aa59df92549cec5c4338df1d1da3ed5a75f28be94567","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-12-08T04:16:28Z","title_canon_sha256":"d928473929eaf882f96065e5f44b24b069454a23a6e29388137d05eb40daeaf9"},"schema_version":"1.0","source":{"id":"1912.03612","kind":"arxiv","version":1}},"canonical_sha256":"9988385bffc0b70ff5607cf1e396f440a13b4e24aa2179035e1ea394f198729b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9988385bffc0b70ff5607cf1e396f440a13b4e24aa2179035e1ea394f198729b","first_computed_at":"2026-07-05T00:24:47.098616Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:24:47.098616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vwSRyhf4RnDojdccd1EyX6/Le/hRIMYLP1Mx3HrqVBQXYj3TloNoMfiQr0SFFbF7KeI6ZUwCXd8HrUvyWc4CAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:24:47.099079Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.03612","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25dfe20f2a70f267011e1ffc4678262d0ec6060ce07dd9587ed3d1c683189012","sha256:56345667dfc275cd39d6db4ab148e9dcc4f068ffdc90167ea0f6528c8ba56745"],"state_sha256":"19ba1ba191fe1e6677087259c3ba2ff29ce8bcb3d62e0bfeb4c1890974e65a1f"}